scholarly journals Corrigendum to “Evaluating the performance of CMIP6 Earth system models in simulating global vegetation structure and distribution” [Advance Climate Change Res Volume 12 Issue 4 (2021) 584‒595]

2021 ◽  
Author(s):  
Song Xiang ◽  
Wang Dan-Yun ◽  
Li Fang ◽  
Zeng Xiao-Dong
Keyword(s):  
Climate Change ◽  
Vegetation Structure ◽  
Earth System ◽  
System Models ◽  
Global Vegetation ◽  
Earth System Models

Assessing the capacity of Earth System Models to simulate spatiotemporal variability in fire weather indicators

2021 ◽  
Author(s):  
Carolina Gallo Granizo ◽  
Jonathan Eden ◽  
Bastien Dieppois ◽  
Matthew Blackett
Keyword(s):  
Climate Change ◽  
Spatial Scales ◽  
Fire Danger ◽  
Spatiotemporal Variability ◽  
Global Evaluation ◽  
Fire Weather ◽  
Earth System ◽  
Fire Weather Index ◽  
System Models ◽  
Earth System Models

<p>Weather and climate play an important role in shaping global fire regimes and geographical distributions of burnable areas. At the global scale, fire danger is likely to increase in the near future due to warmer temperatures and changes in precipitation patterns, as projected by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). There is a need to develop the most reliable projections of future climate-driven fire danger to enable decision makers and forest managers to take both targeted proactive actions and to respond to future fire events.</p><p>Climate change projections generated by Earth System Models (ESMs) provide the most important basis for understanding past, present and future changes in the climate system and its impacts. ESMs are, however, subject to systematic errors and biases, which are not fully taken into account when developing risk scenarios for wild fire activity. Projections of climate-driven fire danger have often been limited to the use of single models or the mean of multi-model ensembles, and compared to a single set of observational data (e.g. one index derived from one reanalysis).</p><p>Here, a comprehensive global evaluation of the representation of a series of fire weather indicators in the latest generation of ESMs is presented. Seven fire weather indices from the Canadian Forest Fire Weather Index System were generated using daily fields realisations simulated by 25 ESMs from the 6<sup>th</sup> Coupled Model Intercomparison Project (CMIP6). With reference to observational and reanalysis datasets, we quantify the capacity of each model to realistically simulate the variability, magnitude and spatial extent of fire danger. The highest-performing models are identified and, subsequently, the limitations of combining models based on independency and equal performance when generating fire danger projections are discussed. To conclude, recommendations are given for the development of user- and policy-driven model evaluation at spatial scales relevant for decision-making and forest management.</p>

scholarly journals Resolving ecological feedbacks on the ocean carbon sink in Earth system models

2020 ◽  
Author(s):  
David I. Armstrong McKay ◽  
Sarah E. Cornell ◽  
Katherine Richardson ◽  
Johan Rockström
Keyword(s):  
Climate Change ◽  
Carbon Sink ◽  
Biological Pump ◽  
Earth System ◽  
Temperature Dependent ◽  
System Models ◽  
Plankton Ecology ◽  
Ocean Carbon ◽  
The Impact ◽  
Earth System Models

Abstract. The Earth’s oceans are one of the largest sinks in the Earth system for anthropogenic CO2 emissions, acting as a negative feedback on climate change. Earth system models predict, though, that climate change will lead to a weakening ocean carbon uptake rate as warm water holds less dissolved CO2 and biological productivity declines. However, most Earth system models do not incorporate the impact of warming on bacterial remineralisation and rely on simplified representations of plankton ecology that do not resolve the potential impact of climate change on ecosystem structure or elemental stoichiometry. Here we use a recently-developed extension of the cGEnIE Earth system model (ecoGEnIE) featuring a trait-based scheme for plankton ecology (ECOGEM), and also incorporate cGEnIE's temperature-dependent remineralisation (TDR) scheme. This enables evaluation of the impact of both ecological dynamics and temperature-dependent remineralisation on the soft-tissue biological pump in response to climate change. We find that including TDR strengthens the biological pump relative to default runs due to increased nutrient recycling, while ECOGEM weakens the biological pump by enabling a shift to smaller plankton classes. However, interactions with concurrent ocean acidification cause opposite sign responses for the carbon sink in both cases: TDR leads to a smaller sink relative to default runs whereas ECOGEM leads to a larger sink. Combining TDR and ECOGEM results in a net strengthening of the biological pump and a small net reduction in carbon sink relative to default. These results clearly illustrate the substantial degree to which ecological dynamics and biodiversity modulate the strength of climate-biosphere feedbacks, and demonstrate that Earth system models need to incorporate more ecological complexity in order to resolve carbon sink weakening.

scholarly journals An Overview of CMIP5 and the Experiment Design

2012 ◽  
Vol 93 (4) ◽  
pp. 485-498 ◽  
Author(s):  
Karl E. Taylor ◽  
Ronald J. Stouffer ◽  
Gerald A. Meehl
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Experiment Design ◽  
Global Climate Models ◽  
Model Output ◽  
Earth System ◽  
Intergovernmental Panel ◽  
System Models ◽  
Earth System Models

The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.

Impact of improved land model depth and hydrology on climate change projections

2020 ◽  
Author(s):  
Norman Steinert ◽  
Fidel González-Rouco ◽  
Stefan Hagemann ◽  
Philipp de Vrese ◽  
Elena García-Bustamante ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Earth System ◽  
Energy Propagation ◽  
Near Surface ◽  
Bottom Boundary ◽  
System Models ◽  
Model Component ◽  
And Storage ◽  
Earth System Models

<p>The representation of the thermal and hydrological state in the land model component of Earth System Models is crucial to have a realistic simulation of subsurface processes and the coupling between the atmo-, lito- and biosphere. There is evidence suggesting an inaccurate simulation of subsurface thermodynamics in current-generation Earth System Models, which have Land Surface Models that are too shallow. In simulations with a bottom boundary too close to the surface, the energy propagation and spatio-temporal variability of subsurface temperatures are affected. This potentially restrains the simulation of land-air interactions and subsurface phenomena, e.g. energy/moisture balance and storage capacity, freeze/thaw cycles and permafrost evolution. We introduce modifications for a deeper soil into the JSBACH soil model component of the MPI-ESM for climate projections of the 21st century. Subsurface layers are added progressively to increase the bottom boundary depth from 10m to 1400m. This leads to near-surface cooling of the soil and encourages regional terrestrial energy uptake by one order of magnitude and more. <br>The depth-changes in the soil also have implications for the hydrological regime, in which the moisture between the surface and the bedrock is sensitive to variations in the thermal regime. Additionally, we compare two different global soil parameter datasets that have major implications for the vertical distribution and availability of soil moisture and its exchange with the land surface. The implementation of supercool water and water phase changes in the soil creates a coupling between the soil thermal and hydrological regimes. In both cases of bottom boundary and water depth changes, we explore the sensitivity of JSBACH from the perspective of changes in the soil thermodynamics, energy balance and storage, as well as the effect of including freezing and thawing processes and their influence on the simulation of permafrost areas in the Northern Hemisphere high latitudes. The latter is of particular interest due to their vulnerability to long-term climate change.</p>

scholarly journals Oceanic primary production decline halved in eddy-resolving simulations of global warming

2021 ◽  
Vol 18 (14) ◽  
pp. 4321-4349
Author(s):  
Damien Couespel ◽  
Marina Lévy ◽  
Laurent Bopp
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Primary Production ◽  
Nutrient Transport ◽  
Biogeochemical Model ◽  
Earth System ◽  
System Models ◽  
Marine Biomass ◽  
Fish Catch ◽  
Earth System Models

Abstract. The decline in ocean primary production is one of the most alarming consequences of anthropogenic climate change. This decline could indeed lead to a decrease in marine biomass and fish catch, as highlighted by recent policy-relevant reports. Because of computational constraints, current Earth system models used to project ocean primary production under global warming scenarios have to parameterize flows occurring below the resolution of their computational grid (typically 1∘). To overcome these computational constraints, we use an ocean biogeochemical model in an idealized configuration representing a mid-latitude double-gyre circulation and perform global warming simulations under an increasing horizontal resolution (from 1 to 1/27∘) and under a large range of parameter values for the eddy parameterization employed in the coarse-resolution configuration. In line with projections from Earth system models, all our simulations project a marked decline in net primary production in response to the global warming forcing. Whereas this decline is only weakly sensitive to the eddy parameters in the eddy-parameterized coarse 1∘ resolution simulations, the simulated decline in primary production in the subpolar gyre is halved at the finest eddy-resolving resolution (−12 % at 1/27∘ vs. −26 % at 1∘) at the end of the 70-year-long global warming simulations. This difference stems from the high sensitivity of the sub-surface nutrient transport to model resolution. Although being only one piece of a much broader and more complicated response of the ocean to climate change, our results call for improved representation of the role of eddies in nutrient transport below the seasonal mixed layer to better constrain the future evolution of marine biomass and fish catch potential.

scholarly journals Variable particle size distributions reduce the sensitivity of global export flux to climate change

2021 ◽  
Vol 18 (1) ◽  
pp. 229-250
Author(s):  
Shirley W. Leung ◽  
Thomas Weber ◽  
Jacob A. Cram ◽  
Curtis Deutsch
Keyword(s):  
Climate Change ◽  
Particle Size ◽  
Euphotic Zone ◽  
Nutrient Concentrations ◽  
Biogeochemical Model ◽  
Size Distributions ◽  
Earth System ◽  
Particle Size Distributions ◽  
System Models ◽  
Earth System Models

Abstract. Recent earth system models predict a 10 %–20 % decrease in particulate organic carbon export from the surface ocean by the end of the 21st century due to global climate change. This decline is mainly caused by increased stratification of the upper ocean, resulting in reduced shallow subsurface nutrient concentrations and a slower supply of nutrients to the surface euphotic zone in low latitudes. These predictions, however, do not typically account for associated changes in remineralization depths driven by sinking-particle size. Here we combine satellite-derived export and particle size maps with a simple 3-D global biogeochemical model that resolves dynamic particle size distributions to investigate how shifts in particle size may buffer or amplify predicted changes in surface nutrient supply and therefore export production. We show that higher export rates are empirically correlated with larger sinking particles and presumably larger phytoplankton, particularly in tropical and subtropical regions. Incorporating these empirical relationships into our global model shows that as circulation slows, a decrease in export is associated with a shift towards smaller particles, which sink more slowly and are thus remineralized shallower. This shift towards shallower remineralization in turn leads to greater recycling of nutrients in the upper water column and thus faster nutrient recirculation into the euphotic zone. The end result is a boost in productivity and export that counteracts the initial circulation-driven decreases. This negative feedback mechanism (termed the particle-size–remineralization feedback) slows export decline over the next century by ∼ 14 % globally (from −0.29 to −0.25 GtC yr−1) and by ∼ 20 % in the tropical and subtropical oceans, where export decreases are currently predicted to be greatest. Our findings suggest that to more accurately predict changes in biological pump strength under a warming climate, earth system models should include dynamic particle-size-dependent remineralization depths.

scholarly journals Harmonising plant functional type distributions for evaluating Earth system models

2019 ◽  
Vol 15 (1) ◽  
pp. 335-366 ◽  
Author(s):  
Anne Dallmeyer ◽  
Martin Claussen ◽  
Victor Brovkin
Keyword(s):  
Classical Method ◽  
New Method ◽  
Earth System ◽  
System Models ◽  
Warm Temperate Forest ◽  
Simulated Climate ◽  
Vegetation Models ◽  
Global Vegetation ◽  
Warm Temperate ◽  
Earth System Models

Abstract. Dynamic vegetation models simulate global vegetation in terms of fractional coverage of a few plant functional types (PFTs). Although these models often share the same concept, they differ with respect to the number and kind of PFTs, complicating the comparability of simulated vegetation distributions. Pollen-based vegetation reconstructions are initially only available in the form of time series of individual taxa that are not distinguished in the models. Thus, to evaluate simulated vegetation distributions, the modelling results and pollen-based vegetation reconstructions have to be converted into a comparable format. The classical approach is the method of biomisation, but hitherto PFT-based biomisation methods were only available for individual models. We introduce and evaluate a simple, universally applicable technique to harmonise PFT distributions by assigning them into nine mega-biomes, using only assumptions on the minimum PFT cover fractions and few bioclimatic constraints (based on the 2 m temperature). These constraints mainly follow the limitation rules used in the classical biome models (here BIOME4). We test the method for six state-of-the-art dynamic vegetation models that are included in Earth system models based on pre-industrial, mid-Holocene and Last Glacial Maximum simulations. The method works well, independent of the spatial resolution or the complexity of the models. Large biome belts (such as tropical forest) are generally better represented than regionally confined biomes (warm–temperate forest, savanna). The comparison with biome distributions inferred via the classical biomisation approach of forcing biome models (here BIOME1) with the simulated climate states shows that the PFT-based biomisation is even able to keep up with the classical method. However, as the new method considers the PFT distributions actually calculated by the Earth system models, it allows for a direct comparison and evaluation of simulated vegetation distributions which the classical method cannot do. Thereby, the new method provides a powerful tool for the evaluation of Earth system models in general.

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